Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-05-04

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country

Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-24) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection

Figure 1: Confirmed cases with date of infection on the 2020-04-24 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases

Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-24 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases

Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-24 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions

Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-24 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-24 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-04-24)

Table 1: Latest estimates (as of the 2020-04-24) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.

Country/Region	New confirmed cases by infection date	Expected change in daily cases	Effective reproduction no.	Doubling/halving time (days)
Afghanistan	181 (144 – 214)	Increasing	1.3 (1.2 – 1.5)	12 (8 – 23)
Algeria	178 (145 – 212)	Increasing	1.2 (1.1 – 1.3)	17 (10 – 65)
Argentina	156 (125 – 185)	Likely increasing	1.1 (1 – 1.2)	56 (17 – -40)
Armenia	102 (75 – 126)	Increasing	1.2 (1.1 – 1.5)	15 (8.1 – 150)
Australia	14 (4 – 21)	Unsure	1 (0.5 – 1.4)	-71 (7 – -6)
Austria	69 (51 – 89)	Unsure	1 (0.8 – 1.2)	440 (15 – -16)
Azerbaijan	50 (31 – 66)	Likely increasing	1.2 (0.9 – 1.5)	17 (7.3 – -49)
Bahrain	133 (105 – 160)	Unsure	1.1 (0.9 – 1.2)	200 (17 – -20)
Bangladesh	657 (592 – 715)	Increasing	1.2 (1.1 – 1.3)	16 (12 – 25)
Belarus	1031 (943 – 1107)	Increasing	1.2 (1.1 – 1.2)	23 (17 – 39)
Belgium	631 (568 – 688)	Decreasing	0.8 (0.7 – 0.9)	-14 (-22 – -10)
Bolivia	119 (90 – 144)	Increasing	1.4 (1.2 – 1.5)	11 (6.8 – 27)
Bosnia and Herzegovina	72 (49 – 91)	Increasing	1.4 (1.1 – 1.6)	9.9 (5.9 – 30)
Brazil	6893 (6685 – 7109)	Increasing	1.3 (1.2 – 1.4)	13 (12 – 15)
Bulgaria	55 (35 – 71)	Unsure	1 (0.8 – 1.2)	-41 (22 – -10)
Cameroon	96 (74 – 121)	Unsure	1.1 (0.9 – 1.3)	110 (15 – -21)
Canada	1899 (1800 – 2014)	Increasing	1.1 (1 – 1.1)	44 (27 – 120)
Chile	1153 (1062 – 1241)	Increasing	1.5 (1.3 – 1.6)	8.4 (7.1 – 10)
China	5 (1 – 10)	Likely decreasing	0.7 (0.2 – 1.1)	-7.1 (11 – -2.7)
Colombia	390 (345 – 440)	Increasing	1.2 (1.1 – 1.4)	15 (11 – 27)
Cote dIvoire	48 (32 – 65)	Unsure	1.1 (0.8 – 1.3)	51 (9.7 – -16)
Croatia	12 (4 – 20)	Likely decreasing	0.8 (0.4 – 1.2)	-10 (15 – -3.8)
Cuba	53 (34 – 70)	Unsure	1.1 (0.9 – 1.3)	31 (8.9 – -21)
Czechia	69 (49 – 91)	Unsure	1 (0.7 – 1.2)	-250 (16 – -14)
Democratic Republic of the Congo	53 (34 – 69)	Increasing	1.5 (1.2 – 1.8)	7 (4.4 – 17)
Denmark	158 (127 – 188)	Unsure	1 (0.8 – 1.1)	-110 (29 – -20)
Djibouti	15 (6 – 24)	Unsure	0.8 (0.5 – 1.2)	-38 (8.9 – -6.1)
Dominican Republic	334 (288 – 378)	Increasing	1.3 (1.2 – 1.5)	12 (8.4 – 20)
Ecuador	985 (902 – 1058)	Decreasing	0.6 (0.5 – 0.8)	-7.1 (-19 – -4.4)
Egypt	331 (289 – 379)	Increasing	1.2 (1.1 – 1.3)	17 (11 – 35)
Equatorial Guinea	6 (1 – 12)	Decreasing	0.5 (0.2 – 0.8)	-3 (-8.1 – -1.9)
Estonia	12 (4 – 20)	Unsure	0.9 (0.5 – 1.2)	-15 (11 – -4.4)
Finland	115 (91 – 141)	Unsure	1 (0.9 – 1.2)	100 (17 – -25)
France	1130 (1038 – 1209)	Decreasing	0.9 (0.8 – 1)	-29 (-87 – -17)
Germany	1402 (1304 – 1488)	Decreasing	0.9 (0.9 – 1)	-31 (-140 – -17)
Ghana	145 (115 – 171)	Increasing	1.3 (1.1 – 1.4)	14 (8.6 – 40)
Greece	22 (9 – 32)	Unsure	0.9 (0.6 – 1.3)	-33 (10 – -6.3)
Guinea	94 (70 – 116)	Likely increasing	1.1 (0.9 – 1.3)	44 (13 – -31)
Guinea Bissau	50 (30 – 65)	Increasing	2.1 (1.6 – 2.7)	4 (2.9 – 6.3)
Honduras	80 (53 – 99)	Increasing	1.5 (1.2 – 1.8)	8.1 (5.2 – 17)
Hungary	80 (57 – 103)	Unsure	1 (0.9 – 1.2)	130 (14 – -18)
Iceland	2 (0 – 6)	Unsure	1.2 (0 – 2.5)	-0.73 (0.26 – -0.15)
India	2479 (2349 – 2607)	Increasing	1.2 (1.2 – 1.3)	15 (13 – 19)
Indonesia	394 (341 – 440)	Likely increasing	1.1 (1 – 1.2)	48 (20 – -110)
Iran	1107 (1022 – 1184)	Unsure	1 (0.9 – 1)	-710 (70 – -59)
Iraq	91 (68 – 113)	Increasing	1.4 (1.1 – 1.6)	9.9 (6.2 – 24)
Ireland	354 (304 – 400)	Decreasing	0.8 (0.7 – 0.9)	-13 (-21 – -9.3)
Israel	159 (130 – 187)	Likely decreasing	0.9 (0.7 – 1)	-18 (1100 – -9)
Italy	2228 (2109 – 2338)	Likely decreasing	1 (0.9 – 1)	-52 (-370 – -28)
Japan	289 (245 – 328)	Likely decreasing	0.9 (0.8 – 1)	-30 (170 – -14)
Kazakhstan	236 (199 – 276)	Increasing	1.3 (1.1 – 1.4)	13 (8.8 – 25)
Kosovo	11 (2 – 17)	Decreasing	0.6 (0.3 – 0.8)	-5.1 (-38 – -2.7)
Kuwait	320 (276 – 369)	Increasing	1.3 (1.1 – 1.4)	15 (10 – 27)
Kyrgyzstan	21 (9 – 31)	Unsure	1.1 (0.8 – 1.4)	26 (6.1 – -11)
Latvia	12 (3 – 19)	Unsure	1 (0.6 – 1.4)	-50 (6.7 – -5.3)
Lebanon	6 (1 – 11)	Unsure	1.1 (0.5 – 1.7)	-34 (4.2 – -3.3)
Lithuania	16 (6 – 24)	Unsure	1.1 (0.6 – 1.5)	30 (5.6 – -9)
Luxembourg	19 (8 – 29)	Unsure	1 (0.6 – 1.4)	-120 (8.2 – -7)
Malaysia	87 (65 – 110)	Increasing	1.2 (1 – 1.5)	15 (7.8 – -2200)
Maldives	74 (52 – 94)	Increasing	1.6 (1.3 – 1.9)	7.2 (4.8 – 14)
Mexico	1530 (1434 – 1625)	Increasing	1.2 (1.2 – 1.3)	16 (13 – 22)
Moldova	121 (91 – 145)	Unsure	0.9 (0.8 – 1.1)	-32 (58 – -12)
Morocco	143 (110 – 169)	Unsure	1 (0.8 – 1.1)	-95 (25 – -16)
Netherlands	492 (426 – 541)	Decreasing	0.9 (0.8 – 1)	-20 (-59 – -12)
New Zealand	2 (0 – 6)	Unsure	1.4 (0.2 – 2.5)	-0.97 (1.6 – -0.23)
Niger	9 (2 – 16)	Unsure	1.1 (0.5 – 1.7)	70 (4.6 – -5.4)
Nigeria	244 (208 – 285)	Increasing	1.5 (1.3 – 1.6)	8.4 (6.4 – 12)
North Macedonia	25 (12 – 36)	Unsure	0.9 (0.7 – 1.2)	-42 (11 – -7.4)
Norway	45 (28 – 61)	Likely decreasing	0.9 (0.6 – 1.1)	-20 (35 – -7.7)
Oman	95 (70 – 118)	Unsure	1 (0.9 – 1.1)	120 (16 – -21)
Pakistan	1188 (1103 – 1270)	Increasing	1.3 (1.2 – 1.4)	15 (12 – 21)
Palestine	6 (1 – 11)	Decreasing	0.6 (0.1 – 0.9)	-2.8 (-12 – -1.5)
Panama	256 (213 – 295)	Increasing	1.1 (1 – 1.3)	24 (13 – 120)
Paraguay	38 (24 – 53)	Increasing	2.1 (1.5 – 2.6)	3.9 (2.8 – 6.7)
Peru	3192 (3050 – 3336)	Increasing	1.3 (1.2 – 1.3)	14 (12 – 17)
Philippines	267 (224 – 306)	Increasing	1.2 (1 – 1.3)	22 (13 – 91)
Poland	324 (276 – 370)	Unsure	1 (0.9 – 1.1)	-100 (52 – -25)
Portugal	295 (250 – 334)	Decreasing	0.8 (0.7 – 0.9)	-15 (-27 – -9.9)
Puerto Rico	99 (76 – 122)	Increasing	1.7 (1.4 – 2)	5.5 (4.1 – 8.2)
Qatar	840 (773 – 916)	Likely increasing	1.1 (1 – 1.1)	77 (31 – -160)
Romania	312 (262 – 349)	Unsure	1 (0.9 – 1.1)	-100 (51 – -25)
Russia	8741 (8497 – 9025)	Increasing	1.2 (1.2 – 1.3)	16 (14 – 18)
Saudi Arabia	1524 (1431 – 1623)	Increasing	1.1 (1.1 – 1.2)	27 (20 – 44)
Senegal	87 (62 – 108)	Increasing	1.3 (1.1 – 1.5)	16 (8.3 – 300)
Serbia	245 (204 – 280)	Unsure	1 (0.9 – 1.1)	150 (25 – -36)
Singapore	726 (656 – 793)	Decreasing	0.9 (0.9 – 1)	-38 (-180 – -21)
Slovakia	6 (1 – 11)	Decreasing	0.4 (0.2 – 0.7)	-3.1 (-13 – -1.7)
Somalia	41 (26 – 56)	Unsure	1.1 (0.8 – 1.3)	48 (9.5 – -17)
South Africa	369 (320 – 412)	Increasing	1.3 (1.2 – 1.5)	13 (9.3 – 21)
South Korea	9 (2 – 16)	Unsure	1 (0.5 – 1.6)	-71 (5.8 – -5.1)
Spain	1188 (1101 – 1270)	Decreasing	0.7 (0.6 – 0.8)	-9.7 (-12 – -8.2)
Sri Lanka	25 (11 – 36)	Unsure	0.9 (0.7 – 1.1)	-11 (130 – -5.1)
Sudan	78 (57 – 97)	Increasing	1.6 (1.3 – 1.8)	7.1 (4.9 – 13)
Sweden	699 (630 – 759)	Increasing	1.1 (1 – 1.2)	53 (23 – -180)
Switzerland	152 (119 – 180)	Likely decreasing	0.9 (0.7 – 1.1)	-35 (61 – -14)
Thailand	7 (1 – 13)	Decreasing	0.6 (0.3 – 0.8)	-4.1 (-36 – -2.2)
Tunisia	10 (2 – 18)	Unsure	1 (0.6 – 1.4)	-35 (6.5 – -4.7)
Turkey	2715 (2588 – 2844)	Unsure	1 (0.9 – 1)	-160 (110 – -47)
Ukraine	577 (513 – 636)	Increasing	1.2 (1.1 – 1.3)	20 (12 – 66)
United Arab Emirates	633 (567 – 698)	Increasing	1.1 (1 – 1.2)	33 (19 – 130)
United Kingdom	5960 (5771 – 6176)	Increasing	1.1 (1.1 – 1.2)	27 (20 – 39)
United Republic of Tanzania	36 (19 – 49)	Increasing	1.4 (1 – 1.7)	8.1 (4.5 – 37)
United States of America	33914 (33255 – 34405)	Increasing	1.1 (1.1 – 1.1)	40 (29 – 64)
Uzbekistan	51 (33 – 68)	Unsure	1.1 (0.8 – 1.4)	21 (8 – -32)